Investigating the Impact of Acetone on the Performance and Emissions of Acetone-Butanol-Ethanol (ABE) and Gasoline Blends in an SI Engine

2015 ◽  
Author(s):  
Karthik Nithyanandan ◽  
Jiaxiang Zhang ◽  
Li Yuqiang ◽  
Han Wu ◽  
Chia-Fon Lee
Keyword(s):  
Si Engine ◽  
Performance And Emissions ◽  
Acetone Butanol Ethanol ◽  
The Impact

scholarly journals Application of ANN to predict performance and emissions of SI engine using gasoline-methanol blends

2021 ◽  
Vol 104 (1) ◽  
pp. 003685042110023
Author(s):  
Ehtasham Ahmed ◽  
Muhammad Usman ◽  
Sibghatallah Anwar ◽  
Hafiz Muhammad Ahmad ◽  
Muhammad Waqar Nasir ◽  
...  
Keyword(s):  
Adaptive Learning ◽  
Alternative Fuels ◽  
Exhaust Emissions ◽  
Ann Model ◽  
Si Engine ◽  
Fuel Blends ◽  
Performance And Emissions ◽  
And Performance ◽  
Artificial Neural Network Ann ◽  
The Impact

The deployment of methanol like alternative fuels in engines is a necessity of the present time to comprehend power requirements and environmental pollution. Furthermore, a comprehensive prediction of the impact of the methanol-gasoline blend on engine characteristics is also required in the era of artificial intelligence. The current study analyzes and compares the experimental and Artificial Neural Network (ANN) aided performance and emissions of four-stroke, single-cylinder SI engine using methanol-gasoline blends of 0%, 3%, 6%, 9%, 12%, 15%, and 18%. The experiments were performed at engine speeds of 1300–3700 rpm with constant loads of 20 and 40 psi for seven different fractions of fuels. Further, an ANN model has developed setting fuel blends, speed and load as inputs, and exhaust emissions and performance parameters as the target. The dataset was randomly divided into three groups of training (70%), validation (15%), and testing (15%) using MATLAB. The feedforward algorithm was used with tangent sigmoid transfer active function (tansig) and gradient descent with an adaptive learning method. It was observed that the continuous addition of methanol up to 12% (M12) increased the performance of the engine. However, a reduction in emissions was observed except for NOx emissions. The regression correlation coefficient (R) and the mean relative error (MRE) were in the range of 0.99100–0.99832 and 1.2%–2.4% respectively, while the values of root mean square error were extremely small. The findings depicted that M12 performed better than other fractions. ANN approach was found suitable for accurately predicting the performance and exhaust emissions of small-scaled SI engines.

Performance and Emissions of a Natural Gas Fueled Two-Stroke SI Engine

2008 ◽  
Author(s):  
A. Gimelli ◽  
C. Cascone ◽  
O. Pennacchia ◽  
A. Unich ◽  
P. Capaldi
Keyword(s):  
Natural Gas ◽  
Si Engine ◽  
Performance And Emissions ◽  
Gas Fueled

scholarly journals Review of Performance and Emmissions Characteristics of Bio-Additive Fuel on SI Engine Fuelled by Biopetrol

2015 ◽  
Vol 773-774 ◽  
pp. 430-434
Author(s):  
Azizul Mokhtar ◽  
Nazrul Atan ◽  
Najib Rahman ◽  
Amir Khalid
Keyword(s):  
Fuel Economy ◽  
Fossil Fuels ◽  
Review Paper ◽  
Engine Performance ◽  
Exhaust Emissions ◽  
Spark Ignition Engine ◽  
Si Engine ◽  
New Approach ◽  
Performance And Emission ◽  
Performance And Emissions

Bio-additive is biodegradable and produces less air pollution thus significant for replacing the limited fossil fuels and reducing threats to the environment from exhaust emissions and global warming. Instead, the bio-additives can remarkably improve the fuel economy SI engine while operating on all kinds of fuel. Some of the bio-additive has the ability to reduce the total CO2 emission from internal petrol engine. This review paper focuses to determine a new approach in potential of bio-additives blends operating with bio-petrol on performance and emissions of spark ignition engine. It is shown that the variant in bio-additives blending ratio and engine operational condition are reduced engine-out emissions and increased efficiency. It seems that the bio-additives can increase the maximum cylinder combustion pressure, improve exhaust emissions and largely reduce the friction coefficient. The review concludes that the additives usage in bio-petrol is inseparable for the better engine performance and emission control and further research is needed to develop bio-petrol specific additives.

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